Estimating Cloth Draping Parameters from Range Data

In this paper we present a computer vision algorithm for estimating cloth parameters for modeling. In an analysis-by-synthesis manner, the algorithm compares the drape of the model with the range data and searches for the best fit. It can be applied to any physics-based cloth model. The motivating application is fashion design using CAD systems, but the ability of the algorithm to estimate the shape of the object supporting the scanned cloth, indicates the possibility of utilizing cloth models to overcome problems in human tracking algorithms, caused by clothing. 1. INTRODUCTION Development of physics-based cloth models is very important for textile industry (3D CAD systems for clothing design), computer vision (tracking dressed humans) and virtual reality applications (model-based telepresence). Model parameters can be derived from mechanical measurements obtained by the Kawabata Evaluation System [1], [3]. A quantitative comparison between simulated and real drape has not yet been o…